cs.AI - 人工智能
cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DM - 离散数学 cs.DS - 数据结构与算法 cs.ET - 新兴技术 cs.GT - 计算机科学与博弈论 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.AT - 代数拓扑 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]A Sufficient Statistic for Influence in Structured Multiagent Environments
• [cs.AI]Aggregating Probabilistic Judgments
• [cs.AI]DREAMT — Embodied Motivational Conversational Storytelling
• [cs.AI]Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests
• [cs.AI]Incremental Answer Set Programming with Overgrounding
• [cs.AI]Interpretable Modelling of Driving Behaviors in Interactive Driving Scenarios based on Cumulative Prospect Theory
• [cs.AI]Open Problems in a Logic of Gossips
• [cs.AI]Orometric Methods in Bounded Metric Data
• [cs.AI]Paracoherent Answer Set Semantics meets Argumentation Frameworks
• [cs.AI]Quantifying Similarity between Relations with Fact Distribution
• [cs.AI]Why Build an Assistant in Minecraft?
• [cs.CL]Augmenting a BiLSTM tagger with a Morphological Lexicon and a Lexical Category Identification Step
• [cs.CL]Cultural Endowment as Collective Improvisation: subjectivity and digital infinity
• [cs.CL]Discourse-Based Evaluation of Language Understanding
• [cs.CL]ELI5: Long Form Question Answering
• [cs.CL]Emotion Detection in Text: Focusing on Latent Representation
• [cs.CL]Exploring sentence informativeness
• [cs.CL]Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-based Detection
• [cs.CL]Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation
• [cs.CL]Incremental Transformer with Deliberation Decoder for Document Grounded Conversations
• [cs.CL]Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs
• [cs.CL]Learning dynamic word embeddings with drift regularisation
• [cs.CL]Syntax-aware Neural Semantic Role Labeling
• [cs.CL]The Unbearable Weight of Generating Artificial Errors for Grammatical Error Correction
• [cs.CL]Using Word Embeddings to Examine Gender Bias in Dutch Newspapers, 1950-1990
• [cs.CL]VIFIDEL: Evaluating the Visual Fidelity of Image Descriptions
• [cs.CL]What is this Article about? Extreme Summarization with Topic-aware Convolutional Neural Networks
• [cs.CR]ER-AE: Differentially-private Text Generation for Authorship Anonymization
• [cs.CR]Next Generation Resilient Cyber-Physical Systems
• [cs.CR]On the Information Privacy Model: the Group and Composition Privacy
• [cs.CR]Privacy-Preserving Blockchain Mining: Sybil-resistance by Proof-of-Useful-Work
• [cs.CV]A Single Image based Head Pose Estimation Method with Spherical Parameterization
• [cs.CV]Adapting Computer Vision Algorithms for Omnidirectional Video
• [cs.CV]An Efficient 3D CNN for Action/Object Segmentation in Video
• [cs.CV]An Efficient Method of Detection and Recognition in Remote Sensing Image Based on multi-angle Region of Interests
• [cs.CV]An Interpretable Compression and Classification System: Theory and Applications
• [cs.CV]Automated Surgical Activity Recognition with One Labeled Sequence
• [cs.CV]Automatic detection of multiple pathologies in fundus photographs using spin-off learning
• [cs.CV]Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images
• [cs.CV]Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention
• [cs.CV]Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night
• [cs.CV]Deep Learning Approaches for Image Retrieval and Pattern Spotting in Ancient Documents
• [cs.CV]DeepIris: Iris Recognition Using A Deep Learning Approach
• [cs.CV]DetectFusion: Detecting and Segmenting Both Known and Unknown Dynamic Objects in Real-time SLAM
• [cs.CV]Domain-Specific Priors and Meta Learning for Low-shot First-Person Action Recognition
• [cs.CV]Extended Local Binary Patterns for Efficient and Robust Spontaneous Facial Micro-Expression Recognition
• [cs.CV]Feature Graph Learning for 3D Point Cloud Denoising
• [cs.CV]Human Extraction and Scene Transition utilizing Mask R-CNN
• [cs.CV]Image Classification with Hierarchical Multigraph Networks
• [cs.CV]Image-and-Spatial Transformer Networks for Structure-Guided Image Registration
• [cs.CV]ImageNet-trained deep neural network exhibits illusion-like response to the Scintillating Grid
• [cs.CV]Markerless Augmented Advertising for Sports Videos
• [cs.CV]Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks
• [cs.CV]Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes
• [cs.CV]Order Matters: Shuffling Sequence Generation for Video Prediction
• [cs.CV]PH-GCN: Person Re-identification with Part-based Hierarchical Graph Convolutional Network
• [cs.CV]Pan-tilt-zoom SLAM for Sports Videos
• [cs.CV]Polyp Detection and Segmentation using Mask R-CNN: Does a Deeper Feature Extractor CNN Always Perform Better?
• [cs.CV]Quadruplet Selection Methods for Deep Embedding Learning
• [cs.CV]RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques
• [cs.CV]Real-time Background-aware 3D Textureless Object Pose Estimation
• [cs.CV]Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders
• [cs.CV]Satellite-Net: Automatic Extraction of Land Cover Indicators from Satellite Imagery by Deep Learning
• [cs.CV]Sensor Aware Lidar Odometry
• [cs.CV]Shallow Unorganized Neural Networks using Smart Neuron Model for Visual Perception
• [cs.CV]TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition
• [cs.CV]Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
• [cs.CV]Unsupervised Segmentation of Hyperspectral Images Using 3D Convolutional Autoencoders
• [cs.CV]Visualizing the Invisible: Occluded Vehicle Segmentation and Recovery
• [cs.CV]signADAM: Learning Confidences for Deep Neural Networks
• [cs.CY]A Simple Sinuosity-Based Method using GPS data to Support Mitigation Policies for Public Buses GHG Emissions
• [cs.CY]Elementary Interactions An Approach in Decision Tool Development
• [cs.DB]Fast Record Linkage for Company Entities
• [cs.DB]Linked Crunchbase: A Linked Data API and RDF Data Set About Innovative Companies
• [cs.DC]Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference
• [cs.DC]Extending the ARC Information Providers to report information on GPU resources
• [cs.DC]Properties of Decentralized Consensus Technology — Why not every Blockchain is a Blockchain
• [cs.DM]Logical Classification of Partially Ordered Data
• [cs.DM]Stochastic-Greedy++: Closing the Optimality Gap in Exact Weak Submodular Maximization
• [cs.DS]Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit
• [cs.DS]Optimal In-place Algorithms for Basic Graph Problems
• [cs.ET]Fundamental aspects of noise in analog-hardware neural networks
• [cs.ET]Non-STDP based Unsupervised Memristive Neural Networks with High Hardware Compatibility
• [cs.GT]A Conceptually Well-Founded Characterization of Iterated Admissibility Using an “All I Know” Operator
• [cs.GT]Exploiting Belief Bases for Building Rich Epistemic Structures
• [cs.GT]Measuring Belief and Risk Attitude
• [cs.IR]A Conceptual Framework for Evaluating Fairness in Search
• [cs.IR]Combinatorial Keyword Recommendations for Sponsored Search with Deep Reinforcement Learning
• [cs.IR]Learning More From Less: Towards Strengthening Weak Supervision for Ad-Hoc Retrieval
• [cs.IT]Adaptive Release Duration Modulation for Limited Molecule Production and Storage
• [cs.IT]Block-sparse Recovery of Semidefinite Systems and Generalized Null Space Conditions
• [cs.IT]Cuboid Partitioning for Hierarchical Coded Matrix Multiplication
• [cs.IT]Deep Learning Assisted Sum-Product Detection Algorithm for Faster-than-Nyquist Signaling
• [cs.IT]Deterministic Sampling Decoding: Where Sphere Decoding Meets Lattice Gaussian Distribution
• [cs.IT]Early Acceptance Matching Game for User Association in 5G Cellular HetNet
• [cs.IT]Energy efficient coded random access for the wireless uplink
• [cs.IT]Expectation Propagation Line Spectral Estimation
• [cs.IT]Hierarchical Coded Matrix Multiplication
• [cs.IT]Joint Fronthaul Multicast and Cooperative Beamforming for Cache-Enabled Cloud-Based Small Cell Networks: An MDS Codes-Aided Approach
• [cs.IT]Model-Driven Deep Learning for Joint MIMO Channel Estimation and Signal Detection
• [cs.IT]Multi-Layer Transformed MDS Codes with Optimal Repair Access and Low Sub-Packetization
• [cs.IT]Optimal Design of Queuing Systems via Compositional Stochastic Programming
• [cs.IT]Relay-aided Random Access for Energy-Limited Devices in the IoT
• [cs.IT]Root-Hadamard transforms and complementary sequences
• [cs.LG]Adaptive Weight Decay for Deep Neural Networks
• [cs.LG]Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network
• [cs.LG]D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction
• [cs.LG]Decentralized Deep Learning with Arbitrary Communication Compression
• [cs.LG]Deep Learning for Time Series Forecasting: The Electric Load Case
• [cs.LG]Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
• [cs.LG]Distributed physics informed neural network for data-efficient solution to partial differential equations
• [cs.LG]Efficient Novelty-Driven Neural Architecture Search
• [cs.LG]Efficient Policy Learning for Non-Stationary MDPs under Adversarial Manipulation
• [cs.LG]EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles
• [cs.LG]FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
• [cs.LG]High Dimensional Bayesian Optimization via Supervised Dimension Reduction
• [cs.LG]Hyperparameter Optimisation with Early Termination of Poor Performers
• [cs.LG]Improving Skip-Gram based Graph Embeddings via Centrality-Weighted Sampling
• [cs.LG]Infant Mortality Prediction using Birth Certificate Data
• [cs.LG]Log-linear models independence structure comparison
• [cs.LG]Online optimization of piecewise Lipschitz functions in changing environments
• [cs.LG]Potential-Based Advice for Stochastic Policy Learning
• [cs.LG]SentiMATE: Learning to play Chess through Natural Language Processing
• [cs.LG]Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics
• [cs.LG]Spectral-based Graph Convolutional Network for Directed Graphs
• [cs.LG]Techniques for Automated Machine Learning
• [cs.LG]The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations
• [cs.LG]Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function
• [cs.LG]Understanding Adversarial Robustness Through Loss Landscape Geometries
• [cs.LG]Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model
• [cs.LO]A Unified Algebraic Framework for Non-Monotonicity
• [cs.LO]Abstract Solvers for Computing Cautious Consequences of ASP programs
• [cs.LO]Founded (Auto)Epistemic Equilibrium Logic Satisfies Epistemic Splitting
• [cs.MA]Aggregation in Value-Based Argumentation Frameworks
• [cs.MA]Causality and Epistemic Reasoning in Byzantine Multi-Agent Systems
• [cs.MA]Comparative Evaluation of Multiagent Learning Algorithms in a Diverse Set of Ad Hoc Team Problems
• [cs.MA]Today Me, Tomorrow Thee: Efficient Resource Allocation in Competitive Settings using Karma Games
• [cs.NE]A Simple Yet Effective Approach to Robust Optimization Over Time
• [cs.NE]A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology
• [cs.NE]Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours using a Quality Diversity Algorithm
• [cs.NE]Improving Neural Network Classifier using Gradient-based Floating Centroid Method
• [cs.NE]Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
• [cs.NI]VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications
• [cs.PL]Towards Verified Stochastic Variational Inference for Probabilistic Programs
• [cs.PL]Towards meta-interpretive learning of programming language semantics
• [cs.RO]A novel object slicing based grasp planner for 3D object grasping using underactuated robot gripper
• [cs.RO]ADAPS: Autonomous Driving Via Principled Simulations
• [cs.RO]Footstep Planning for Autonomous Walking Over Rough Terrain
• [cs.RO]Generating Optimal Grasps Under A Stress-Minimizing Metric
• [cs.RO]Hardware-In-the-Loop for Connected Automated Vehicles Testing in Real Traffic
• [cs.RO]Inferring Occluded Geometry Improves Performance when Retrieving an Object from Dense Clutter
• [cs.RO]Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty
• [cs.RO]Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling Salesman Problem
• [cs.RO]RobustTP: End-to-End Trajectory Prediction for Heterogeneous Road-Agents in Dense Traffic with Noisy Sensor Inputs
• [cs.RO]Speeding Up Iterative Closest Point Using Stochastic Gradient Descent
• [cs.SD]Leveraging Knowledge Bases And Parallel Annotations For Music Genre Translation
• [cs.SE]Feature-Model-Guided Online Learning for Self-Adaptive Systems
• [cs.SE]Learning the Relation between Code Features and Code Transforms with Structured Prediction
• [cs.SE]Structure-Invariant Testing for Machine Translation
• [cs.SI]A Comprehensive Analysis of Twitter Trending Topics
• [cs.SI]Detecting Cyberbullying and Cyberaggression in Social Media
• [cs.SI]Overlapping community detection in networks based on link partitioning and partitioning around medoids
• [cs.SI]Towards an LSTM-based Predictive Framework for Literature-based Knowledge Discovery
• [cs.SI]Trusses and Trapezes: Easily-Interpreted Communities in Social Networks
• [econ.EM]On the simulation of the Hawkes process via Lambert-W functions
• [eess.IV]A Retina-inspired Sampling Method for Visual Texture Reconstruction
• [eess.IV]Automated Muscle Segmentation from Clinical CT using Bayesian U-Net for Personalization of a Musculoskeletal Model
• [eess.IV]Automatic Radiology Report Generation based on Multi-view Image Fusion and Medical Concept Enrichment
• [eess.IV]FD-FCN: 3D Fully Dense and Fully Convolutional Network for Semantic Segmentation of Brain Anatomy
• [eess.IV]Probabilistic Point Cloud Reconstructions for Vertebral Shape Analysis
• [eess.IV]Scene-and-Process-Dependent Spatial Image Quality Metrics
• [eess.IV]Validation of Modulation Transfer Functions and Noise Power Spectra from Natural Scenes
• [eess.IV]k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations
• [eess.SP]A-Phase classification using convolutional neural networks
• [eess.SP]Fast Convolutional Dictionary Learning off the Grid
• [eess.SP]Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks
• [eess.SP]Realistic Channel Models Pre-training
• [eess.SY]Alice’s Adventures in the Markovian World
• [math.AT]Persistence Homology of Networks: Methods and Applications
• [math.OC]Adaptive Susceptibility and Heterogeneity in Contagion Models on Networks
• [math.OC]Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I
• [math.OC]Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization
• [math.PR]Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality
• [math.ST]Convergence Rates of Posterior Distributions in Markov Decision Process
• [math.ST]Cramér-Rao Bounds for Complex-Valued Independent Component Extraction: Determined and Piecewise Determined Mixing Models
• [math.ST]Estimating the Algorithmic Variance of Randomized Ensembles via the Bootstrap
• [math.ST]Extent of occurrence reconstruction using a new data-driven support estimator
• [math.ST]Fair quantile regression
• [math.ST]Fast rates for empirical risk minimization with cadlag losses with bounded sectional variation norm
• [math.ST]Nonparametric Estimation of the Trend in Reflected Fractional SDE
• [math.ST]On a conjecture by Ben-Akiva and Lerman about the nested logit model
• [physics.comp-ph]Artificial Neural Network Algorithm based Skyrmion Material Design of Chiral Crystals
• [physics.soc-ph]Graph centrality is a question of scale
• [q-bio.NC]Learning spatiotemporal signals using a recurrent spiking network that discretizes time
• [stat.AP]A novel regularized approach for functional data clustering: An application to milking kinetics in dairy goats
• [stat.AP]A state space approach to dynamic modeling of mouse-tracking data
• [stat.AP]Dual Proxy Gaussian Process Stack: Integrating Benthic $δ^{18}{\rm{O}}$ and Radiocarbon Proxies for Inferring Ages on Ocean Sediment Cores
• [stat.AP]Evaluation of the performance of Euro-CORDEX RCMs for assessing hydrological climate change impacts in Great Britain: a comparison of different spatial resolutions and quantile mapping bias correction methods
• [stat.CO]Properties of the Stochastic Approximation EM Algorithm with Mini-batch Sampling
• [stat.ME]A Note on Exploratory Item Factor Analysis by Singular Value Decomposition
• [stat.ME]A Pseudo-Marginal Metropolis-Hastings Algorithm for Estimating Generalized Linear Models in the Presence of Missing Data
• [stat.ME]Bayesian estimation of probabilistic sensitivity measures
• [stat.ME]Efficient Bayesian PARCOR Approaches for Dynamic Modeling of Multivariate Time Series
• [stat.ME]Trend detection in GEV models
• [stat.ML]Accelerating Experimental Design by Incorporating Experimenter Hunches
• [stat.ML]Conscientious Classification: A Data Scientist’s Guide to Discrimination-Aware Classification
• [stat.ML]Fully Unsupervised Feature Alignment for Critical System Health Monitoring with Varied Operating Conditions
• [stat.ML]Noise Regularization for Conditional Density Estimation
• [stat.ML]Some New Results for Poisson Binomial Models
• [stat.ML]Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model
• [stat.ML]Surfing: Iterative optimization over incrementally trained deep networks
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• [cs.AI]A Sufficient Statistic for Influence in Structured Multiagent Environments
Frans A. Oliehoek, Stefan Witwicki, Leslie P. Kaelbling
http://arxiv.org/abs/1907.09278v1
• [cs.AI]Aggregating Probabilistic Judgments
Magdalena Ivanovska, Marija Slavkovik
http://arxiv.org/abs/1907.09111v1
• [cs.AI]DREAMT — Embodied Motivational Conversational Storytelling
David M W Powers
http://arxiv.org/abs/1907.09293v1
• [cs.AI]Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests
Taoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang
http://arxiv.org/abs/1907.08739v1
• [cs.AI]Incremental Answer Set Programming with Overgrounding
Francesco Calimeri, Giovambattista Ianni, Francesco Pacenza, Simona Perri, Jessica Zangari
http://arxiv.org/abs/1907.09212v1
• [cs.AI]Interpretable Modelling of Driving Behaviors in Interactive Driving Scenarios based on Cumulative Prospect Theory
Liting Sun, Wei Zhan, Yeping Hu, Masayoshi Tomizuka
http://arxiv.org/abs/1907.08707v1
• [cs.AI]Open Problems in a Logic of Gossips
Krzysztof R. Apt, Dominik Wojtczak
http://arxiv.org/abs/1907.09097v1
• [cs.AI]Orometric Methods in Bounded Metric Data
Maximilian Stubbemann, Tom Hanika, Gerd Stumme
http://arxiv.org/abs/1907.09239v1
• [cs.AI]Paracoherent Answer Set Semantics meets Argumentation Frameworks
Giovanni Amendola, Francesco Ricca
http://arxiv.org/abs/1907.09426v1
• [cs.AI]Quantifying Similarity between Relations with Fact Distribution
Weize Chen, Hao Zhu, Xu Han, Zhiyuan Liu, Maosong Sun
http://arxiv.org/abs/1907.08937v1
• [cs.AI]Why Build an Assistant in Minecraft?
Arthur Szlam, Jonathan Gray, Kavya Srinet, Yacine Jernite, Armand Joulin, Gabriel Synnaeve, Douwe Kiela, Haonan Yu, Zhuoyuan Chen, Siddharth Goyal, Demi Guo, Danielle Rothermel, C. Lawrence Zitnick, Jason Weston
http://arxiv.org/abs/1907.09273v1
• [cs.CL]Augmenting a BiLSTM tagger with a Morphological Lexicon and a Lexical Category Identification Step
Steinþór Steingrímsson, Örvar Kárason, Hrafn Loftsson
http://arxiv.org/abs/1907.09038v1
• [cs.CL]Cultural Endowment as Collective Improvisation: subjectivity and digital infinity
Victor Peterson II
http://arxiv.org/abs/1907.08643v1
• [cs.CL]Discourse-Based Evaluation of Language Understanding
Damien Sileo, Tim Van-de-Cruys, Camille Pradel, Philippe Muller
http://arxiv.org/abs/1907.08672v1
• [cs.CL]ELI5: Long Form Question Answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, Michael Auli
http://arxiv.org/abs/1907.09190v1
• [cs.CL]Emotion Detection in Text: Focusing on Latent Representation
Armin Seyeditabari, Narges Tabari, Shafie Gholizadeh, Wlodek Zadrozny
http://arxiv.org/abs/1907.09369v1
• [cs.CL]Exploring sentence informativeness
Syrielle Montariol, Aina Garí Soler, Alexandre Allauzen
http://arxiv.org/abs/1907.08469v2
• [cs.CL]Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-based Detection
David Ifeoluwa Adelani, Haotian Mai, Fuming Fang, Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
http://arxiv.org/abs/1907.09177v1
• [cs.CL]Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation
Shantipriya Parida, Ondřej Bojar, Satya Ranjan Dash
http://arxiv.org/abs/1907.08948v1
• [cs.CL]Incremental Transformer with Deliberation Decoder for Document Grounded Conversations
Zekang Li, Cheng Niu, Fandong Meng, Yang Feng, Qian Li, Jie Zhou
http://arxiv.org/abs/1907.08854v1
• [cs.CL]Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs
Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann, Asja Fischer
http://arxiv.org/abs/1907.09361v1
• [cs.CL]Learning dynamic word embeddings with drift regularisation
Syrielle Montariol, Alexandre Allauzen
http://arxiv.org/abs/1907.09169v1
• [cs.CL]Syntax-aware Neural Semantic Role Labeling
Qingrong Xia, Zhenghua Li, Min Zhang, Meishan Zhang, Guohong Fu, Rui Wang, Luo Si
http://arxiv.org/abs/1907.09312v1
• [cs.CL]The Unbearable Weight of Generating Artificial Errors for Grammatical Error Correction
Phu Mon Htut, Joel Tetreault
http://arxiv.org/abs/1907.08889v1
• [cs.CL]Using Word Embeddings to Examine Gender Bias in Dutch Newspapers, 1950-1990
Melvin Wevers
http://arxiv.org/abs/1907.08922v1
• [cs.CL]VIFIDEL: Evaluating the Visual Fidelity of Image Descriptions
Pranava Madhyastha, Josiah Wang, Lucia Specia
http://arxiv.org/abs/1907.09340v1
• [cs.CL]What is this Article about? Extreme Summarization with Topic-aware Convolutional Neural Networks
Shashi Narayan, Shay B. Cohen, Mirella Lapata
http://arxiv.org/abs/1907.08722v1
• [cs.CR]ER-AE: Differentially-private Text Generation for Authorship Anonymization
Haohan Bo, Steven H. H. Ding, Benjamin C. M. Fung, Farkhund Iqbal
http://arxiv.org/abs/1907.08736v1
• [cs.CR]Next Generation Resilient Cyber-Physical Systems
Michel Barbeau, Georg Carle, Joaquin Garcia-Alfaro, Vicenç Torra
http://arxiv.org/abs/1907.08849v1
• [cs.CR]On the Information Privacy Model: the Group and Composition Privacy
Genqiang Wu
http://arxiv.org/abs/1907.09311v1
• [cs.CR]Privacy-Preserving Blockchain Mining: Sybil-resistance by Proof-of-Useful-Work
Hjalmar Turesson, Alexandra Roatis, Marek Laskowski, Henry Kim
http://arxiv.org/abs/1907.08744v1
• [cs.CV]A Single Image based Head Pose Estimation Method with Spherical Parameterization
Hui Yuana, Mengyu Lia, Junhui Hou, Jimin Xiao
http://arxiv.org/abs/1907.09217v1
• [cs.CV]Adapting Computer Vision Algorithms for Omnidirectional Video
Hannes Fassold
http://arxiv.org/abs/1907.09233v1
• [cs.CV]An Efficient 3D CNN for Action/Object Segmentation in Video
Rui Hou, Chen Chen, Rahul Sukthankar, Mubarak Shah
http://arxiv.org/abs/1907.08895v1
• [cs.CV]An Efficient Method of Detection and Recognition in Remote Sensing Image Based on multi-angle Region of Interests
Hongyu Wang, Wei Liang, Guangcun Shan
http://arxiv.org/abs/1907.09320v1
• [cs.CV]An Interpretable Compression and Classification System: Theory and Applications
Tzu-Wei Tseng, Kai-Jiun Yang, C. -C. Jay Kuo, Shang-Ho, Tsai
http://arxiv.org/abs/1907.08952v1
• [cs.CV]Automated Surgical Activity Recognition with One Labeled Sequence
Robert DiPietro, Gregory D. Hager
http://arxiv.org/abs/1907.08825v1
• [cs.CV]Automatic detection of multiple pathologies in fundus photographs using spin-off learning
Gwenolé Quellec, Mathieu Lamard, Pierre-Henri Conze, Pascale Massin, Béatrice Cochener
http://arxiv.org/abs/1907.09449v1
• [cs.CV]Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images
Amir Hossein Raffiee, Humayun Irshad
http://arxiv.org/abs/1907.09081v1
• [cs.CV]Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention
Yuxiao Chen, Long Zhao, Xi Peng, Jianbo Yuan, Dimitris N. Metaxas
http://arxiv.org/abs/1907.08871v1
• [cs.CV]Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night
Vinicius F. Arruda, Thiago M. Paixão, Rodrigo F. Berriel, Alberto F. De Souza, Claudine Badue, Nicu Sebe, Thiago Oliveira-Santos
http://arxiv.org/abs/1907.08719v1
• [cs.CV]Deep Learning Approaches for Image Retrieval and Pattern Spotting in Ancient Documents
Kelly Lais Wiggers, Alceu de Souza Britto Junior, Alessandro Lameiras Koerich, Laurent Heutte, Luiz Eduardo Soares de Oliveira
http://arxiv.org/abs/1907.09404v1
• [cs.CV]DeepIris: Iris Recognition Using A Deep Learning Approach
Shervin Minaee, Amirali Abdolrashidi
http://arxiv.org/abs/1907.09380v1
• [cs.CV]DetectFusion: Detecting and Segmenting Both Known and Unknown Dynamic Objects in Real-time SLAM
Ryo Hachiuma, Christian Pirchheim, Dieter Schmalstieg, Hideo Saito
http://arxiv.org/abs/1907.09127v1
• [cs.CV]Domain-Specific Priors and Meta Learning for Low-shot First-Person Action Recognition
Huseyin Coskun, Zeeshan Zia, Bugra Tekin, Federica Bogo, Nassir Navab, Federico Tombari, Harpreet Sawhney
http://arxiv.org/abs/1907.09382v1
• [cs.CV]Extended Local Binary Patterns for Efficient and Robust Spontaneous Facial Micro-Expression Recognition
Chengyu Guo, Jingyun Liang, Geng Zhan, Zhong Liu, Matti Pietikäinen, Li Liu
http://arxiv.org/abs/1907.09160v1
• [cs.CV]Feature Graph Learning for 3D Point Cloud Denoising
Wei Hu, Xiang Gao, Gene Cheung, Zongming Guo
http://arxiv.org/abs/1907.09138v1
• [cs.CV]Human Extraction and Scene Transition utilizing Mask R-CNN
Asati Minkesh, Kraittipong Worranitta, Miyachi Taizo
http://arxiv.org/abs/1907.08884v1
• [cs.CV]Image Classification with Hierarchical Multigraph Networks
Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor
http://arxiv.org/abs/1907.09000v1
• [cs.CV]Image-and-Spatial Transformer Networks for Structure-Guided Image Registration
Matthew C. H. Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker
http://arxiv.org/abs/1907.09200v1
• [cs.CV]ImageNet-trained deep neural network exhibits illusion-like response to the Scintillating Grid
Eric D. Sun, Ron Dekel
http://arxiv.org/abs/1907.09019v1
• [cs.CV]Markerless Augmented Advertising for Sports Videos
Hallee E. Wong, Osman Akar, Emmanuel Antonio Cuevas, Iuliana Tabian, Divyaa Ravichandran, Iris Fu, Cambron Carter
http://arxiv.org/abs/1907.09394v1
• [cs.CV]Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks
Shao-Yuan Lo, Hsueh-Ming Hang, Sheng-Wei Chan, Jing-Jhih Lin
http://arxiv.org/abs/1907.09438v1
• [cs.CV]Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes
Jingru Yi, Pengxiang Wu, Qiaoying Huang, Hui Qu, Bo Liu, Daniel J. Hoeppner, Dimitris N. Metaxas
http://arxiv.org/abs/1907.09140v1
• [cs.CV]Order Matters: Shuffling Sequence Generation for Video Prediction
Junyan Wang, Bingzhang Hu, Yang Long, Yu Guan
http://arxiv.org/abs/1907.08845v1
• [cs.CV]PH-GCN: Person Re-identification with Part-based Hierarchical Graph Convolutional Network
Bo Jiang, Xixi Wang, Bin Luo
http://arxiv.org/abs/1907.08822v1
• [cs.CV]Pan-tilt-zoom SLAM for Sports Videos
Jikai Lu, Jianhui Chen, James J. Little
http://arxiv.org/abs/1907.08816v1
• [cs.CV]Polyp Detection and Segmentation using Mask R-CNN: Does a Deeper Feature Extractor CNN Always Perform Better?
Hemin Ali Qadir, Younghak Shin, Johannes Solhusvik, Jacob Bergsland, Lars Aabakken, Ilangko Balasingham
http://arxiv.org/abs/1907.09180v1
• [cs.CV]Quadruplet Selection Methods for Deep Embedding Learning
Kaan Karaman, Erhan Gundogdu, Aykut Koc, A. Aydin Alatan
http://arxiv.org/abs/1907.09245v1
• [cs.CV]RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques
Isaac Ronald Ward, Hamid Laga, Mohammed Bennamoun
http://arxiv.org/abs/1907.09236v1
• [cs.CV]Real-time Background-aware 3D Textureless Object Pose Estimation
Mang Shao, Danhang Tang, Tae-Kyun Kim
http://arxiv.org/abs/1907.09128v1
• [cs.CV]Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders
Markus Roland Ernst, Jochen Triesch, Thomas Burwick
http://arxiv.org/abs/1907.08831v1
• [cs.CV]Satellite-Net: Automatic Extraction of Land Cover Indicators from Satellite Imagery by Deep Learning
Eleonora Bernasconi, Francesco Pugliese, Diego Zardetto, Monica Scannapieco
http://arxiv.org/abs/1907.09423v1
• [cs.CV]Sensor Aware Lidar Odometry
Dmitri Kovalenko, Mikhail Korobkin, Andrey Minin
http://arxiv.org/abs/1907.09167v1
• [cs.CV]Shallow Unorganized Neural Networks using Smart Neuron Model for Visual Perception
Richard Jiang, Danny Crookes
http://arxiv.org/abs/1907.09050v1
• [cs.CV]TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition
Mina Bishay, Georgios Zoumpourlis, Ioannis Patras
http://arxiv.org/abs/1907.09021v1
• [cs.CV]Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
Aditya Mogadala, Marimuthu Kalimuthu, Dietrich Klakow
http://arxiv.org/abs/1907.09358v1
• [cs.CV]Unsupervised Segmentation of Hyperspectral Images Using 3D Convolutional Autoencoders
Jakub Nalepa, Michal Myller, Yasuteru Imai, Ken-ichi Honda, Tomomi Takeda, Marek Antoniak
http://arxiv.org/abs/1907.08870v1
• [cs.CV]Visualizing the Invisible: Occluded Vehicle Segmentation and Recovery
Xiaosheng Yan, Yuanlong Yu, Feigege Wang, Wenxi Liu, Shengfeng He, Jia Pan
http://arxiv.org/abs/1907.09381v1
• [cs.CV]signADAM: Learning Confidences for Deep Neural Networks
Dong Wang, Yicheng Liu, Wenwo Tang, Fanhua Shang, Hongying Liu, Qigong Sun, Licheng Jiao
http://arxiv.org/abs/1907.09008v1
• [cs.CY]A Simple Sinuosity-Based Method using GPS data to Support Mitigation Policies for Public Buses GHG Emissions
William Wills, Joao Meirelles, Vivien Green Baptista, Gabriel Cury, Pablo Cerdeira
http://arxiv.org/abs/1907.09335v1
• [cs.CY]Elementary Interactions An Approach in Decision Tool Development
Heinrich Söbke, Andrea Lück
http://arxiv.org/abs/1907.08699v1
• [cs.DB]Fast Record Linkage for Company Entities
Thomas Gschwind, Christoph Miksovic, Katsiaryna Mirylenka, Paolo Scotton
http://arxiv.org/abs/1907.08667v1
• [cs.DB]Linked Crunchbase: A Linked Data API and RDF Data Set About Innovative Companies
Michael Färber
http://arxiv.org/abs/1907.08671v1
• [cs.DC]Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference
Weiwen Jiang, Edwin H. -M. Sha, Xinyi Zhang, Lei Yang, Qingfeng Zhuge, Yiyu Shi, Jingtong Hu
http://arxiv.org/abs/1907.08985v1
• [cs.DC]Extending the ARC Information Providers to report information on GPU resources
Max Isacson, Mattias Ellert, Richard Brenner
http://arxiv.org/abs/1907.09272v1
• [cs.DC]Properties of Decentralized Consensus Technology — Why not every Blockchain is a Blockchain
Christopher Ehmke, Florian Blum, Volker Gruhn
http://arxiv.org/abs/1907.09289v1
• [cs.DM]Logical Classification of Partially Ordered Data
Elena V. Djukova, Gleb O. Masliakov, Petr A. Prokofyev
http://arxiv.org/abs/1907.08962v1
• [cs.DM]Stochastic-Greedy++: Closing the Optimality Gap in Exact Weak Submodular Maximization
Gustavo de Veciana, Abolfazl Hashemi, Haris Vikalo
http://arxiv.org/abs/1907.09064v1
• [cs.DS]Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit
Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi
http://arxiv.org/abs/1907.08743v1
• [cs.DS]Optimal In-place Algorithms for Basic Graph Problems
Sankardeep Chakraborty, Kunihiko Sadakane, Srinivasa Rao Satti
http://arxiv.org/abs/1907.09280v1
• [cs.ET]Fundamental aspects of noise in analog-hardware neural networks
Nadezhda Semenova, Xavier Porte, Louis Andreoli, Maxime Jacquot, Laurent Larger, Daniel Brunner
http://arxiv.org/abs/1907.09002v1
• [cs.ET]Non-STDP based Unsupervised Memristive Neural Networks with High Hardware Compatibility
Zhiri Tang, Yanhua Chen, Hao Wang, Jin He, Qijun Huang, Sheng Chang
http://arxiv.org/abs/1907.09126v1
• [cs.GT]A Conceptually Well-Founded Characterization of Iterated Admissibility Using an “All I Know” Operator
Joseph Y. Halpern, Rafael Pass
http://arxiv.org/abs/1907.09106v1
• [cs.GT]Exploiting Belief Bases for Building Rich Epistemic Structures
Emiliano Lorini
http://arxiv.org/abs/1907.09114v1
• [cs.GT]Measuring Belief and Risk Attitude
Sven Neth
http://arxiv.org/abs/1907.09115v1
• [cs.IR]A Conceptual Framework for Evaluating Fairness in Search
Anubrata Das, Matthew Lease
http://arxiv.org/abs/1907.09328v1
• [cs.IR]Combinatorial Keyword Recommendations for Sponsored Search with Deep Reinforcement Learning
Zhipeng Li, Jianwei Wu, Lin Sun, Tao Rong
http://arxiv.org/abs/1907.08686v1
• [cs.IR]Learning More From Less: Towards Strengthening Weak Supervision for Ad-Hoc Retrieval
Dany Haddad, Joydeep Ghosh
http://arxiv.org/abs/1907.08657v1
• [cs.IT]Adaptive Release Duration Modulation for Limited Molecule Production and Storage
Ladan Khaloopour, Mahtab Mirmohseni, Masoumeh Nasiri-Kenari
http://arxiv.org/abs/1907.08934v1
• [cs.IT]Block-sparse Recovery of Semidefinite Systems and Generalized Null Space Conditions
Janin Heuer, Frederic Matter, Marc E. Pfetsch, Thorsten Theobald
http://arxiv.org/abs/1907.09442v1
• [cs.IT]Cuboid Partitioning for Hierarchical Coded Matrix Multiplication
Shahrzad Kiani, Nuwan Ferdinand, Stark C. Draper
http://arxiv.org/abs/1907.08819v1
• [cs.IT]Deep Learning Assisted Sum-Product Detection Algorithm for Faster-than-Nyquist Signaling
Bryan Liu, Shuangyang Li, Yixuan Xie, Jinhong Yuan
http://arxiv.org/abs/1907.09225v1
• [cs.IT]Deterministic Sampling Decoding: Where Sphere Decoding Meets Lattice Gaussian Distribution
Zheng Wang, Cong Ling, Shi Jin
http://arxiv.org/abs/1907.09119v1
• [cs.IT]Early Acceptance Matching Game for User Association in 5G Cellular HetNet
Alireza Alizadeh, Mai Vu
http://arxiv.org/abs/1907.08867v1
• [cs.IT]Energy efficient coded random access for the wireless uplink
Suhas S Kowshik, Kirill Andreev, Alexey Frolov, Yury Polyanskiy
http://arxiv.org/abs/1907.09448v1
• [cs.IT]Expectation Propagation Line Spectral Estimation
Jiang Zhu, Mihai Alin Badiu
http://arxiv.org/abs/1907.09094v1
• [cs.IT]Hierarchical Coded Matrix Multiplication
Shahrzad Kiani, Nuwan Ferdinand, Stark C. Draper
http://arxiv.org/abs/1907.08818v1
• [cs.IT]Joint Fronthaul Multicast and Cooperative Beamforming for Cache-Enabled Cloud-Based Small Cell Networks: An MDS Codes-Aided Approach
Xiongwei Wu, Qiang Li, Victor C. M. Leung, P. C. Ching
http://arxiv.org/abs/1907.08756v1
• [cs.IT]Model-Driven Deep Learning for Joint MIMO Channel Estimation and Signal Detection
Hengtao He, Chao-Kai Wen, Shi Jin, Geoffrey Ye Li
http://arxiv.org/abs/1907.09439v1
• [cs.IT]Multi-Layer Transformed MDS Codes with Optimal Repair Access and Low Sub-Packetization
Hanxu Hou, Patrick P. C. Lee, Yunghsiang S. Han
http://arxiv.org/abs/1907.08938v1
• [cs.IT]Optimal Design of Queuing Systems via Compositional Stochastic Programming
Srujan Teja Thomdapu, Ketan Rajawat
http://arxiv.org/abs/1907.08774v1
• [cs.IT]Relay-aided Random Access for Energy-Limited Devices in the IoT
Jinho Choi
http://arxiv.org/abs/1907.09084v1
• [cs.IT]Root-Hadamard transforms and complementary sequences
Luis A. Medina, Matthew G. Parker, Constanza Riera, Pantelimon Stanica
http://arxiv.org/abs/1907.09360v1
• [cs.LG]Adaptive Weight Decay for Deep Neural Networks
Kensuke Nakamura, Byung-Woo Hong
http://arxiv.org/abs/1907.08931v1
• [cs.LG]Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network
Martin Gleize, Eyal Shnarch, Leshem Choshen, Lena Dankin, Guy Moshkowich, Ranit Aharonov, Noam Slonim
http://arxiv.org/abs/1907.08971v1
• [cs.LG]D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction
Divya Saxena, Jiannong Cao
http://arxiv.org/abs/1907.08556v2
• [cs.LG]Decentralized Deep Learning with Arbitrary Communication Compression
Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi
http://arxiv.org/abs/1907.09356v1
• [cs.LG]Deep Learning for Time Series Forecasting: The Electric Load Case
Alberto Gasparin, Slobodan Lukovic, Cesare Alippi
http://arxiv.org/abs/1907.09207v1
• [cs.LG]Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
Lei Lei, Yue Tan, Shiwen Liu, Kan Zheng, Xuemin, Shen
http://arxiv.org/abs/1907.09059v1
• [cs.LG]Distributed physics informed neural network for data-efficient solution to partial differential equations
Vikas Dwivedi, Nishant Parashar, Balaji Srinivasan
http://arxiv.org/abs/1907.08967v1
• [cs.LG]Efficient Novelty-Driven Neural Architecture Search
Miao Zhang, Huiqi Li, Shirui Pan, Taoping Liu, Steven Su
http://arxiv.org/abs/1907.09109v1
• [cs.LG]Efficient Policy Learning for Non-Stationary MDPs under Adversarial Manipulation
Tiancheng Yu, Suvrit Sra
http://arxiv.org/abs/1907.09350v1
• [cs.LG]EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles
Besher Alhalabi, Mohamed Medhat Gaber, Shadi Basurra
http://arxiv.org/abs/1907.09286v1
• [cs.LG]FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
Yiqiang Chen, Jindong Wang, Chaohui Yu, Wen Gao, Xin Qin
http://arxiv.org/abs/1907.09173v1
• [cs.LG]High Dimensional Bayesian Optimization via Supervised Dimension Reduction
Miao Zhang, Huiqi Li, Steven Su
http://arxiv.org/abs/1907.08953v1
• [cs.LG]Hyperparameter Optimisation with Early Termination of Poor Performers
Dobromir Marinov, Daniel Karapetyan
http://arxiv.org/abs/1907.08651v1
• [cs.LG]Improving Skip-Gram based Graph Embeddings via Centrality-Weighted Sampling
Pedro Almagro-Blanco, Fernando Sancho-Caparrini
http://arxiv.org/abs/1907.08793v1
• [cs.LG]Infant Mortality Prediction using Birth Certificate Data
Antonia Saravanou, Clemens Noelke, Nicholas Huntington, Dolores Acevedo-Garcia, Dimitrios Gunopulos
http://arxiv.org/abs/1907.08968v1
• [cs.LG]Log-linear models independence structure comparison
Jan Strappa, Facundo Bromberg
http://arxiv.org/abs/1907.08892v1
• [cs.LG]Online optimization of piecewise Lipschitz functions in changing environments
Maria-Florina Balcan, Travis Dick, Dravyansh Sharma
http://arxiv.org/abs/1907.09137v1
• [cs.LG]Potential-Based Advice for Stochastic Policy Learning
Baicen Xiao, Bhaskar Ramasubramanian, Andrew Clark, Hannaneh Hajishirzi, Linda Bushnell, Radha Poovendran
http://arxiv.org/abs/1907.08823v1
• [cs.LG]SentiMATE: Learning to play Chess through Natural Language Processing
Isaac Kamlish, Isaac Bentata Chocron, Nicholas McCarthy
http://arxiv.org/abs/1907.08321v2
• [cs.LG]Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics
Khushbu Agarwal, Tome Eftimov, Raghavendra Addanki, Sutanay Choudhury, Suzanne Tamang, Robert Rallo
http://arxiv.org/abs/1907.08650v1
• [cs.LG]Spectral-based Graph Convolutional Network for Directed Graphs
Yi Ma, Jianye Hao, Yaodong Yang, Han Li, Junqi Jin, Guangyong Chen
http://arxiv.org/abs/1907.08990v1
• [cs.LG]Techniques for Automated Machine Learning
Yi-Wei Chen, Qingquan Song, Xia Hu
http://arxiv.org/abs/1907.08908v1
• [cs.LG]The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations
Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, Marcin Detyniecki
http://arxiv.org/abs/1907.09294v1
• [cs.LG]Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function
Stephen Odaibo
http://arxiv.org/abs/1907.08956v1
• [cs.LG]Understanding Adversarial Robustness Through Loss Landscape Geometries
Vinay Uday Prabhu, Dian Ang Yap, Joyce Xu, John Whaley
http://arxiv.org/abs/1907.09061v1
• [cs.LG]Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová
http://arxiv.org/abs/1907.08226v2
• [cs.LO]A Unified Algebraic Framework for Non-Monotonicity
Nourhan Ehab, Haythem O. Ismail
http://arxiv.org/abs/1907.09103v1
• [cs.LO]Abstract Solvers for Computing Cautious Consequences of ASP programs
Giovanni Amendola, Carmine Dodaro, Marco Maratea
http://arxiv.org/abs/1907.09402v1
• [cs.LO]Founded (Auto)Epistemic Equilibrium Logic Satisfies Epistemic Splitting
Jorge Fandinno
http://arxiv.org/abs/1907.09247v1
• [cs.MA]Aggregation in Value-Based Argumentation Frameworks
Grzegorz Lisowski, Sylvie Doutre, Umberto Grandi
http://arxiv.org/abs/1907.09113v1
• [cs.MA]Causality and Epistemic Reasoning in Byzantine Multi-Agent Systems
Roman Kuznets, Laurent Prosperi, Ulrich Schmid, Krisztina Fruzsa
http://arxiv.org/abs/1907.09112v1
• [cs.MA]Comparative Evaluation of Multiagent Learning Algorithms in a Diverse Set of Ad Hoc Team Problems
Stefano V. Albrecht, Subramanian Ramamoorthy
http://arxiv.org/abs/1907.09189v1
• [cs.MA]Today Me, Tomorrow Thee: Efficient Resource Allocation in Competitive Settings using Karma Games
Andrea Censi, Saverio Bolognani, Julian G. Zilly, Shima Sadat Mousavi, Emilio Frazzoli
http://arxiv.org/abs/1907.09198v1
• [cs.NE]A Simple Yet Effective Approach to Robust Optimization Over Time
Lukáš Adam, Xin Yao
http://arxiv.org/abs/1907.09248v1
• [cs.NE]A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology
Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang
http://arxiv.org/abs/1907.09077v1
• [cs.NE]Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours using a Quality Diversity Algorithm
Leo Cazenille, Nicolas Bredeche, José Halloy
http://arxiv.org/abs/1907.09209v1
• [cs.NE]Improving Neural Network Classifier using Gradient-based Floating Centroid Method
Mazharul Islam, Shuangrong Liu, Lin Wang, Xiaojing Zhang
http://arxiv.org/abs/1907.08996v1
• [cs.NE]Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
Jörg Stork, Martin Zaefferer, Thomas Bartz-Beielstein, A. E. Eiben
http://arxiv.org/abs/1907.09300v1
• [cs.NI]VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications
Taylan Şahin, Ramin Khalili, Mate Boban, Adam Wolisz
http://arxiv.org/abs/1907.09319v1
• [cs.PL]Towards Verified Stochastic Variational Inference for Probabilistic Programs
Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang
http://arxiv.org/abs/1907.08827v1
• [cs.PL]Towards meta-interpretive learning of programming language semantics
Sándor Bartha, James Cheney
http://arxiv.org/abs/1907.08834v1
• [cs.RO]A novel object slicing based grasp planner for 3D object grasping using underactuated robot gripper
IA Sainul, Sankha Deb, AK Deb
http://arxiv.org/abs/1907.09142v1
• [cs.RO]ADAPS: Autonomous Driving Via Principled Simulations
Weizi Li, David Wolinski, Ming C. Lin
http://arxiv.org/abs/1907.08874v1
• [cs.RO]Footstep Planning for Autonomous Walking Over Rough Terrain
Robert J. Griffin, Georg Wiedebach, Stephen McCrory, Sylvain Bertrand, Inho Lee, Jerry Pratt
http://arxiv.org/abs/1907.08673v1
• [cs.RO]Generating Optimal Grasps Under A Stress-Minimizing Metric
Zherong Pan, Xifeng Gao, Dinesh Manocha
http://arxiv.org/abs/1907.08749v1
• [cs.RO]Hardware-In-the-Loop for Connected Automated Vehicles Testing in Real Traffic
Yeojun Kim, Samuel Tay, Jacopo Guanetti, Francesco Borrelli, Ryan Miller
http://arxiv.org/abs/1907.09052v1
• [cs.RO]Inferring Occluded Geometry Improves Performance when Retrieving an Object from Dense Clutter
Andrew Price, Linyi Jin, Dmitry Berenson
http://arxiv.org/abs/1907.08770v1
• [cs.RO]Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty
Ajinkya Jain, Scott Niekum
http://arxiv.org/abs/1907.09014v1
• [cs.RO]Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling Salesman Problem
Rik Bähnemann, Nicholas Lawrance, Jen Jen Chung, Michael Pantic, Roland Siegwart, Juan Nieto
http://arxiv.org/abs/1907.09224v1
• [cs.RO]RobustTP: End-to-End Trajectory Prediction for Heterogeneous Road-Agents in Dense Traffic with Noisy Sensor Inputs
Rohan Chandra, Uttaran Bhattacharya, Christian Roncal, Aniket Bera, Dinesh Manocha
http://arxiv.org/abs/1907.08752v1
• [cs.RO]Speeding Up Iterative Closest Point Using Stochastic Gradient Descent
Fahira Afzal Maken, Fabio Ramos, Lionel Ott
http://arxiv.org/abs/1907.09133v1
• [cs.SD]Leveraging Knowledge Bases And Parallel Annotations For Music Genre Translation
Elena V. Epure, Anis Khlif, Romain Hennequin
http://arxiv.org/abs/1907.08698v1
• [cs.SE]Feature-Model-Guided Online Learning for Self-Adaptive Systems
Andreas Metzger, Clément Quinton, Zoltán Ádám Mann, Luciano Baresi, Klaus Pohl
http://arxiv.org/abs/1907.09158v1
• [cs.SE]Learning the Relation between Code Features and Code Transforms with Structured Prediction
Zhongxing Yu, Matias Martinez, Tegawendé F. Bissyandé, Martin Monperrus
http://arxiv.org/abs/1907.09282v1
• [cs.SE]Structure-Invariant Testing for Machine Translation
Pinjia He, Clara Meister, Zhendong Su
http://arxiv.org/abs/1907.08710v1
• [cs.SI]A Comprehensive Analysis of Twitter Trending Topics
Issa Annamoradnejad, Jafar Habibi
http://arxiv.org/abs/1907.09007v1
• [cs.SI]Detecting Cyberbullying and Cyberaggression in Social Media
Despoina Chatzakou, Ilias Leontiadis, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, Athena Vakali, Nicolas Kourtellis
http://arxiv.org/abs/1907.08873v1
• [cs.SI]Overlapping community detection in networks based on link partitioning and partitioning around medoids
Alexander Ponomarenko, Leonidas Pitsoulis, Marat Shamshetdinov
http://arxiv.org/abs/1907.08731v1
• [cs.SI]Towards an LSTM-based Predictive Framework for Literature-based Knowledge Discovery
Nazim Choudhury, Fahim Faisal, Matloob Khushi
http://arxiv.org/abs/1907.09395v1
• [cs.SI]Trusses and Trapezes: Easily-Interpreted Communities in Social Networks
Jonathan D. Cohen
http://arxiv.org/abs/1907.09417v1
• [econ.EM]On the simulation of the Hawkes process via Lambert-W functions
Martin Magris
http://arxiv.org/abs/1907.09162v1
• [eess.IV]A Retina-inspired Sampling Method for Visual Texture Reconstruction
Lin Zhu, Siwei Dong, Tiejun Huang, Yonghong Tian
http://arxiv.org/abs/1907.08769v1
• [eess.IV]Automated Muscle Segmentation from Clinical CT using Bayesian U-Net for Personalization of a Musculoskeletal Model
Yuta Hiasa, Yoshito Otake, Masaki Takao, Takeshi Ogawa, Nobuhiko Sugano, Yoshinobu Sato
http://arxiv.org/abs/1907.08915v1
• [eess.IV]Automatic Radiology Report Generation based on Multi-view Image Fusion and Medical Concept Enrichment
Jianbo Yuan, Haofu Liao, Rui Luo, Jiebo Luo
http://arxiv.org/abs/1907.09085v1
• [eess.IV]FD-FCN: 3D Fully Dense and Fully Convolutional Network for Semantic Segmentation of Brain Anatomy
Binbin Yang, Weiwei Zhang
http://arxiv.org/abs/1907.09194v1
• [eess.IV]Probabilistic Point Cloud Reconstructions for Vertebral Shape Analysis
Anjany Sekuboyina, Markus Rempfler, Alexander Valentinitsch, Maximilian Loeffler, Jan S. Kirschke, Bjoern H. Menze
http://arxiv.org/abs/1907.09254v1
• [eess.IV]Scene-and-Process-Dependent Spatial Image Quality Metrics
Edward W. S. Fry, Sophie Triantaphillidou, Robin B. Jenkin, Ralph E. Jacobson, John R. Jarvis
http://arxiv.org/abs/1907.08926v1
• [eess.IV]Validation of Modulation Transfer Functions and Noise Power Spectra from Natural Scenes
Edward W. S. Fry, Sophie Triantaphillidou, Robin B. Jenkin, John R. Jarvis, Ralph E. Jacobson
http://arxiv.org/abs/1907.08924v1
• [eess.IV]k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations
Chen Qin, Jo Schlemper, Jinming Duan, Gavin Seegoolam, Anthony Price, Joseph Hajnal, Daniel Rueckert
http://arxiv.org/abs/1907.09425v1
• [eess.SP]A-Phase classification using convolutional neural networks
Edgar R. Arce-Santana, Alfonso Alba, Martin O. Mendez, Valdemar Arce-Guevara
http://arxiv.org/abs/1907.09296v1
• [eess.SP]Fast Convolutional Dictionary Learning off the Grid
Andrew H. Song, Francisco J. Flores, Demba Ba
http://arxiv.org/abs/1907.09063v1
• [eess.SP]Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks
Qiang Li, Jin Lei, Jingran Lin, Xiaoxiao Wu
http://arxiv.org/abs/1907.08759v1
• [eess.SP]Realistic Channel Models Pre-training
Yourui Huangfu, Jian Wang, Chen Xu, Rong Li, Yiqun Ge, Xianbin Wang, Huazi Zhang, Jun Wang
http://arxiv.org/abs/1907.09117v1
• [eess.SY]Alice’s Adventures in the Markovian World
Zhanzhan Zhao, Haoran Sun
http://arxiv.org/abs/1907.08981v1
• [math.AT]Persistence Homology of Networks: Methods and Applications
Mehmet Emin Aktas, Esra Akbas, Ahmed El Fatmaoui
http://arxiv.org/abs/1907.08708v1
• [math.OC]Adaptive Susceptibility and Heterogeneity in Contagion Models on Networks
Renato Pagliara, Naomi E. Leonard
http://arxiv.org/abs/1907.08829v1
• [math.OC]Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I
Sandeep Kumar, Ketan Rajawat, Daniel P. Palomar
http://arxiv.org/abs/1907.08969v1
• [math.OC]Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization
Adithya M. Devraj, Jianshu Chen
http://arxiv.org/abs/1907.09150v1
• [math.PR]Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality
Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu
http://arxiv.org/abs/1907.08883v1
• [math.ST]Convergence Rates of Posterior Distributions in Markov Decision Process
Zhen Li, Eric Laber
http://arxiv.org/abs/1907.09083v1
• [math.ST]Cramér-Rao Bounds for Complex-Valued Independent Component Extraction: Determined and Piecewise Determined Mixing Models
Václav Kautský, Zbyněk Koldovský, Petr Tichavský, Vicente Zarzoso
http://arxiv.org/abs/1907.08790v1
• [math.ST]Estimating the Algorithmic Variance of Randomized Ensembles via the Bootstrap
Miles E. Lopes
http://arxiv.org/abs/1907.08742v1
• [math.ST]Extent of occurrence reconstruction using a new data-driven support estimator
A. Rodríguez-Casal, P. Saavedra-Nieves
http://arxiv.org/abs/1907.08627v1
• [math.ST]Fair quantile regression
Dana Yang, John Lafferty, David Pollard
http://arxiv.org/abs/1907.08646v1
• [math.ST]Fast rates for empirical risk minimization with cadlag losses with bounded sectional variation norm
Aurélien F. Bibaut, Mark J. van der Laan
http://arxiv.org/abs/1907.09244v1
• [math.ST]Nonparametric Estimation of the Trend in Reflected Fractional SDE
Nicolas Marie
http://arxiv.org/abs/1907.09232v1
• [math.ST]On a conjecture by Ben-Akiva and Lerman about the nested logit model
Alfred Galichon
http://arxiv.org/abs/1907.08766v1
• [physics.comp-ph]Artificial Neural Network Algorithm based Skyrmion Material Design of Chiral Crystals
B. U. V Prashanth, Mohammed Riyaz Ahmed
http://arxiv.org/abs/1907.09314v1
• [physics.soc-ph]Graph centrality is a question of scale
Alexis Arnaudon, Robert L. Peach, Mauricio Barahona
http://arxiv.org/abs/1907.08624v1
• [q-bio.NC]Learning spatiotemporal signals using a recurrent spiking network that discretizes time
Amadeus Maes, Mauricio Barahona, Claudia Clopath
http://arxiv.org/abs/1907.08801v1
• [stat.AP]A novel regularized approach for functional data clustering: An application to milking kinetics in dairy goats
C. Denis, E. Lebarbier, C. Lévy-Leduc, O. Martin, L. Sansonnet
http://arxiv.org/abs/1907.09192v1
• [stat.AP]A state space approach to dynamic modeling of mouse-tracking data
Antonio Calcagnì, Luigi Lombardi, Marco D’Alessandro
http://arxiv.org/abs/1907.08387v2
• [stat.AP]Dual Proxy Gaussian Process Stack: Integrating Benthic $δ^{18}{\rm{O}}$ and Radiocarbon Proxies for Inferring Ages on Ocean Sediment Cores
Taehee Lee, Lorraine E. Lisiecki, Devin Rand, Geoffrey Gebbie, Charles E. Lawrence
http://arxiv.org/abs/1907.08738v1
• [stat.AP]Evaluation of the performance of Euro-CORDEX RCMs for assessing hydrological climate change impacts in Great Britain: a comparison of different spatial resolutions and quantile mapping bias correction methods
Ernesto Pasten-Zapata, Julie Jones, Helen Moggridge, Martin Widmann
http://arxiv.org/abs/1907.09043v1
• [stat.CO]Properties of the Stochastic Approximation EM Algorithm with Mini-batch Sampling
Estelle Kuhn, Catherine Matias, Tabea Rebafka
http://arxiv.org/abs/1907.09164v1
• [stat.ME]A Note on Exploratory Item Factor Analysis by Singular Value Decomposition
Haoran Zhang, Yunxiao Chen, Xiaoou Li
http://arxiv.org/abs/1907.08713v1
• [stat.ME]A Pseudo-Marginal Metropolis-Hastings Algorithm for Estimating Generalized Linear Models in the Presence of Missing Data
Taylor R. Brown, Timothy L. McMurry, Alexander Langevin
http://arxiv.org/abs/1907.09090v1
• [stat.ME]Bayesian estimation of probabilistic sensitivity measures
Isadora Antoniano-Villalobos, Emanuele Borgonovo, Xuefei Lu
http://arxiv.org/abs/1907.09424v1
• [stat.ME]Efficient Bayesian PARCOR Approaches for Dynamic Modeling of Multivariate Time Series
Wenjie Zhao, Raquel Prado
http://arxiv.org/abs/1907.08733v1
• [stat.ME]Trend detection in GEV models
László Németh, Zuzana Hübnerová, András Zempléni
http://arxiv.org/abs/1907.09435v1
• [stat.ML]Accelerating Experimental Design by Incorporating Experimenter Hunches
Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin, Teo Slezak, Murray Height, Mazher Mohammed, Ian Gibson
http://arxiv.org/abs/1907.09065v1
• [stat.ML]Conscientious Classification: A Data Scientist’s Guide to Discrimination-Aware Classification
Brian d’Alessandro, Cathy O’Neil, Tom LaGatta
http://arxiv.org/abs/1907.09013v1
• [stat.ML]Fully Unsupervised Feature Alignment for Critical System Health Monitoring with Varied Operating Conditions
Gabriel Michau, Olga Fink
http://arxiv.org/abs/1907.09204v1
• [stat.ML]Noise Regularization for Conditional Density Estimation
Jonas Rothfuss, Fabio Ferreira, Simon Boehm, Simon Walther, Maxim Ulrich, Tamim Asfour, Andreas Krause
http://arxiv.org/abs/1907.08982v1
• [stat.ML]Some New Results for Poisson Binomial Models
Evan Rosenman
http://arxiv.org/abs/1907.09053v1
• [stat.ML]Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model
Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu
http://arxiv.org/abs/1907.08880v1
• [stat.ML]Surfing: Iterative optimization over incrementally trained deep networks
Ganlin Song, Zhou Fan, John Lafferty
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